Yearly Traffic Safety Analysis

11,426 CRASHES IN
OHIO, OH
2024

All metrics benchmarked against2023

In 2024, Lucas County recorded 11,426 total crashes, a 3.2% decrease from the 11,803 crashes reported in 2023. The most significant year-over-year change was a 32.1% reduction in total fatalities, which fell from 53 in 2023 to 36 in 2024.

11,426

▼ -3.2%was 11,803

Total Crash Events

36

▼ -32.1%was 53

Persons Killed

4,197

▼ -5.8%was 4,457

Persons Injured

2,684

▼ -8.4%was 2,931

Hit-and-Run Crashes

Note: "Persons Killed" (36) counts individual fatalities across all crash events. "Fatal" in the severity table below (30) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic safety trends in Lucas County showed improvement year-over-year. Total crashes fell by 3.2%, from 11,803 in 2023 to 11,426 in 2024. This decline was accompanied by a 5.8% decrease in total injuries and a notable 32.1% decrease in fatalities.

2,684

Hit-and-Run Crashes — 2024

▼ -8.4% vs prior (2,931)

The number of hit-and-run incidents in Lucas County decreased in 2024 compared to the previous year. There were 2,684 hit-and-run crashes in 2024, down from 2,931 in 2023. This corresponds to a drop in the hit-and-run rate, which fell from 24.8% of all crashes in 2023 to 23.5% in 2024, indicating a downward trend for this crash type.

Vulnerable Road User Casualties

5

Pedestrians Killed

Prior: 7↓-28.6%

31

Motorists Killed

Prior: 46↓-32.6%

120

Pedestrians Injured

Prior: 110↑9.1%

4,077

Motorists Injured

Prior: 4,347↓-6.2%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes in Lucas County remained largely consistent year-over-year. Friday was the peak day for crashes in both 2024 (1,958 crashes) and 2023 (1,930 crashes). The peak hour for collisions shifted slightly earlier, from the 4 p.m. hour in 2023 (1,022 crashes) to the 3 p.m. hour in 2024 (1,024 crashes), with the afternoon commute period continuing to see the highest frequency of incidents.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The overall severity of crashes in Lucas County decreased from 2023 to 2024. The number of fatal crashes fell from 51 to 30, and their share of all crashes dropped from 0.4% to 0.3%. The proportion of crashes resulting in serious injuries remained unchanged at 1.8% in both periods. Correspondingly, crashes resulting in no injuries increased slightly, accounting for 74.9% of all incidents in 2024 compared to 74.3% in the prior year.

Severity is per crash event (most severe injury). 30 fatal crash events resulted in 36 persons killed.

Outcome by Severity (Crash Events)

Fatal30fatal crashes0.3%
↓-41.2%prior 51
Serious Injury210serious injury crashes1.8%
↑1.0%prior 208
Minor Injury1,454minor injury crashes12.7%
↓-0.8%prior 1,466
Possible Injury1,173possible injury crashes10.3%
↓-10.5%prior 1,310
No Injury8,559no injury crashes74.9%
↓-2.4%prior 8,768

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Crash conditions in 2024 were broadly similar to those in 2023, with most incidents occurring in clear weather and daylight on dry roads. There was a slight shift away from adverse conditions year-over-year. Crashes in the rain decreased, accounting for 10.2% of the total in 2024, down from 12.0% in 2023. Similarly, collisions on wet road surfaces fell from 20.4% to 18.1% of all crashes.

Weather

Clear7,671 (67.1%)
↑1.3%prior 7,574
Cloudy1,993 (17.4%)
↓-9.0%prior 2,191
Rain1,170 (10.2%)
↓-17.6%prior 1,420
Snow371 (3.2%)
↓-2.6%prior 381
Other/Unknown122 (1.1%)
↓-9.6%prior 135
Fog; Smog; Smoke58 (0.5%)
↓-10.8%prior 65
Freezing Rain or Freezing Drizzle29 (0.3%)
↑52.6%prior 19
Sleet; Hail9 (0.1%)
↓-10.0%prior 10
Severe Crosswinds3 (0.0%)
↓-50.0%prior 6

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight7,656 (67.0%)
↓-2.1%prior 7,821
Dark - Lighted Roadway2,409 (21.1%)
↓-6.3%prior 2,570
Dawn/Dusk677 (5.9%)
↓-1.5%prior 687
Dark - Roadway Not Lighted493 (4.3%)
↓-3.9%prior 513
Dark - Unknown Roadway Lighting112 (1.0%)
↓-17.0%prior 135
Other/Unknown79 (0.7%)
↑2.6%prior 77

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry8,797 (77.0%)
↓-0.9%prior 8,873
Wet2,068 (18.1%)
↓-14.1%prior 2,408
Snow247 (2.2%)
↓-6.1%prior 263
Ice195 (1.7%)
↑46.6%prior 133
Other/Unknown104 (0.9%)
↓-3.7%prior 108
Sand; Mud; Dirt; Oil; Gravel11 (0.1%)
↑37.5%prior 8
Slush4 (0.0%)
↓-50.0%prior 8

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The composition of vehicles involved in crashes remained stable between 2023 and 2024. The top five vehicle makes involved in collisions were identical in both years: Chevrolet, Ford, Dodge, Jeep, and Honda, with each showing a decrease in total incidents consistent with the overall trend. An analysis of the age of persons involved in crashes shows a consistent distribution, with no significant shifts in representation among age groups year-over-year. For example, the 16-20 age group accounted for 10.3% of persons involved in crashes in both periods.

Top Vehicle Makes (21,710 vehicles)

1
CHEVROLET3,366 (15.5%)
↓-2.5%prior 3,452
2
FORD3,262 (15%)
↓-2.5%prior 3,346
3
DODGE1,685 (7.8%)
↓-11.5%prior 1,904
4
JEEP1,514 (7%)
↓-3.1%prior 1,562
5
HONDA1,442 (6.6%)
↓-6.6%prior 1,544
6
TOYOTA1,079 (5%)
↑4.6%prior 1,032
7
KIA844 (3.9%)
↓-0.6%prior 849
8
CHRYSLER777 (3.6%)
↓-15.0%prior 914
9
GMC723 (3.3%)
↓-8.1%prior 787
10
NISSAN670 (3.1%)
↓-2.6%prior 688

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

2,692 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (25,511 persons with recorded sex)

Male13,431 (52.6%)
↓-2.5%prior 13,769
Female12,080 (47.4%)
↓-2.6%prior 12,399

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Ohio Crash Data (ODOT TIMS), accessed programmatically via the Csv Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: Csv Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2024-01-01 through 2024-12-31
  • Report generated: July 6, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 11,426
  • Total persons involved: 27,412
  • Total vehicles involved: 21,710

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "ohio, OH Crash Intelligence Report: 2024." Published July 6, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2024-annual-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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